JDS communications最新文献_第9页

The Ruminant Farm Systems (RuFaS) model is a platform to support future research and actions for sustainable dairy farming 反刍动物农场系统（RuFaS）模型是一个支持未来可持续奶牛养殖研究和行动的平台

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0861

K.F. Reed , J.M. Tricarico , S. HekmatiAthar , J.S. Waddell , D.A. Andreen , K.R. Briggs , A. Liu , N.D. Tomlinson , J. Adamchick , V.E. Cabrera , H. Hu , Y. Gong , G.M. Graef , M.R. Villalobos-Barquero , J.P. Oliver , D.V. Nydam , N. Ayache , L. McClintock

The Ruminant Farm Systems (RuFaS) model is an open-source, modular, whole-farm simulation platform designed to support interdisciplinary research, innovation, and decision making in sustainable dairy production. This review outlines RuFaS structure, functionality, current applications, and potential for further development. Through integration of biophysical modules for animal, manure, soil and crop, and feed storage systems, RuFaS enables comprehensive evaluation of management strategies, environmental interventions, and productivity outcomes in a whole-farm context. The RuFaS model facilitates hypothesis testing, multi-objective analysis, scenario evaluation, and identification of research gaps by simulating interactions and trade-offs across biological, environmental, and management domains. The model's current applications include its integration into the Farmers Assuring Responsible Management Environmental Stewardship program for GHG accounting and its use in evaluating innovations in nutrition, breeding, and manure management technologies. Its modular architecture supports rapid prototyping, modeling at different scales, and uncertainty analysis, making it adaptable to diverse research questions and stakeholder needs. Finally, it highlights the critical role its open-source foundation has for promoting transparency, reproducibility, and collaborative development across disciplines. Its transparent development process, hosted on GitHub under a GPLv3 license, invites contributions from across disciplines and institutions. Scientists are encouraged to explore RuFaS as a tool for advancing their own research, contributing to model development, and engaging in a shared effort to improve the sustainability of dairy systems.

反刍动物农场系统（RuFaS）模型是一个开源、模块化的全农场模拟平台，旨在支持可持续乳制品生产中的跨学科研究、创新和决策。本文概述了rufa的结构、功能、当前的应用以及进一步发展的潜力。通过整合动物、粪便、土壤和作物的生物物理模块以及饲料储存系统，RuFaS能够在整个农场的背景下对管理策略、环境干预和生产力结果进行全面评估。RuFaS模型通过模拟生物、环境和管理领域的相互作用和权衡，促进了假设检验、多目标分析、情景评估和研究差距的识别。该模型目前的应用包括将其纳入“农民保证负责任管理环境管理计划”，用于温室气体核算，并用于评估营养、育种和粪肥管理技术的创新。它的模块化架构支持快速原型、不同规模的建模和不确定性分析，使其适应不同的研究问题和利益相关者的需求。最后，它强调了其开源基金会在促进透明度、可再现性和跨学科协作开发方面的关键作用。其透明的开发过程，在GPLv3许可下托管在GitHub上，邀请来自各个学科和机构的贡献。鼓励科学家探索rufa，将其作为推进自身研究的工具，为模型开发做出贡献，并共同努力提高乳制品系统的可持续性。

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引用次数: 0

The Future of Dairy: Introduction 乳制品的未来：引言

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0941

Matthew C. Lucy

引用次数: 0

Cognition of dairy cattle: Implications for animal welfare and dairy science 奶牛的认知：对动物福利和乳制品科学的影响

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0860

Kathryn L. Proudfoot , Thomas Ede , Catherine L. Ryan , Heather W. Neave

The study of dairy cattle cognition has gained increasing attention over the past several decades, offering insights into the relationship between cognition and animal welfare. The objectives of this narrative review are to summarize a selection of studies exploring different cognitive processes in dairy cattle, discuss how these processes relate to common management practices and animal welfare, and identify knowledge gaps to guide future research. We begin with a brief overview of research into how dairy cattle perceive and sense the world around them, followed by a description of different types of learning and memory studied in dairy cattle, including nonassociative and associative learning, as well as short- and long-term memory. We then discuss how researchers have explored cognitive processes in dairy cows to understand their social lives, their ability to cope with challenges, and how they feel under different management conditions. Continued research into dairy cattle cognition is encouraged, including both foundational studies asking questions about the cognitive abilities of dairy cattle, as well as applied questions that can lead to improvements to their housing and management. We end by offering several avenues of future research into the cognition of dairy cattle, including a better understanding of competence and resilience, factors that influence cognition such as sleep and individual differences, as well as other under-investigated topics, such as problem-solving and metacognition.

在过去的几十年里，对奶牛认知的研究越来越受到关注，为认知与动物福利之间的关系提供了见解。这篇叙述性综述的目的是总结一些探索奶牛不同认知过程的研究，讨论这些过程与常见管理实践和动物福利的关系，并确定知识空白以指导未来的研究。我们首先简要概述了奶牛如何感知和感知周围世界的研究，然后描述了奶牛学习和记忆的不同类型，包括非联想学习和联想学习，以及短期和长期记忆。然后，我们讨论了研究人员如何探索奶牛的认知过程，以了解它们的社会生活，它们应对挑战的能力，以及它们在不同管理条件下的感受。鼓励对奶牛认知的持续研究，包括提出奶牛认知能力问题的基础研究，以及可以改善其住房和管理的应用问题。最后，我们提出了未来研究奶牛认知的几种途径，包括更好地理解能力和弹性，影响认知的因素，如睡眠和个体差异，以及其他未被研究的主题，如解决问题和元认知。

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引用次数: 0

The future of big data and artificial intelligence on dairy farms: A proposed dairy data ecosystem 大数据和人工智能在奶牛场的未来：一个拟议的奶牛场数据生态系统

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0843

Miel Hostens , Sébastien Franceschini , Meike van Leerdam , Haiyu Yang , Sabina Pokharel , Enhong Liu , Puchun Niu , Hanlu Zhang , Saba Noor , Kristof Hermans , Matthieu Salamone , Sumit Sharma

The dairy sector should overcome challenges in productivity, sustainability, and data management by adopting intelligent, scalable, and privacy-preserving technological solutions. Adopting data and artificial intelligence (AI) technologies is essential to ensure efficient operations and informed decision making and to keep a competitive market advantage. This paper proposes an integrated, multimodal AI framework to support data-intensive dairy farm operations by leveraging big data principles and advancing them through AI technologies. The proposed architecture incorporates edge computing, autonomous AI agents, and federated learning to enable real-time, privacy-preserving analytics at the farm level and promote knowledge sharing and refinement through research farms and cloud collaboration. Farms collect heterogeneous data, which can be transformed into embeddings for both local inference and cloud analysis. These embeddings form the input of AI agents that support health monitoring, risk prediction, operational optimization, and decision making. Privacy is preserved by sharing only model weights or anonymized data externally. The edge layer handles time-sensitive tasks and communicates with a centralized enterprise cloud hosting global models and distributing updates. A research and development cloud linked to research farms ensures model testing and validation. The entire system is orchestrated by autonomous AI agents that manage data, choose models, and interact with stakeholders, and human oversight ensures safe decisions, as illustrated in the practical use case of mastitis management. This architecture could support data integrity, scalability, and real-time personalization, along with opening up space for partnerships between farms, research institutions, and regulatory bodies to promote secure, cross-sector innovation.

乳制品行业应该通过采用智能、可扩展和保护隐私的技术解决方案来克服生产力、可持续性和数据管理方面的挑战。采用数据和人工智能（AI）技术对于确保高效运营和明智决策以及保持竞争市场优势至关重要。本文提出了一个集成的、多模式的人工智能框架，通过利用大数据原理并通过人工智能技术推进它们来支持数据密集型奶牛场运营。拟议的架构结合了边缘计算、自主人工智能代理和联邦学习，以实现农场层面的实时、隐私保护分析，并通过研究农场和云协作促进知识共享和改进。农场收集异构数据，这些数据可以转化为嵌入，用于本地推理和云分析。这些嵌入构成了支持健康监测、风险预测、操作优化和决策制定的人工智能代理的输入。通过仅对外共享模型权重或匿名数据来保护隐私。边缘层处理时间敏感的任务，并与托管全球模型和分发更新的集中式企业云通信。与研究农场相关联的研发云确保了模型的测试和验证。整个系统由管理数据、选择模型并与利益相关者互动的自主人工智能代理编排，人类监督确保安全决策，如乳腺炎管理的实际用例所示。这种架构可以支持数据完整性、可扩展性和实时个性化，同时为农场、研究机构和监管机构之间的合作开辟空间，以促进安全的跨部门创新。

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引用次数: 0

The future of udder health: Antimicrobial stewardship and alternative therapy of bovine mastitis 乳腺健康的未来：抗菌剂管理和牛乳腺炎的替代疗法

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0839

Pamela L. Ruegg

Although antimicrobial usage is highly restricted in dairy cows, concerns about development and dissemination of resistant bacteria have led to a reexamination of mastitis therapies. In the past, almost all cases of clinical mastitis were treated symptomatically using intramammary antibiotics, and in many regions, most cows received intramammary antibiotic treatments at dry-off. On modern dairy farms, changes in the distribution of etiological agents have reduced the need to give antimicrobials for all mastitis cases. Culture-guided selective treatment protocols for nonsevere clinical mastitis have been adopted on many farms and align with principles of antimicrobial stewardship. Although some antimicrobial therapy is needed to maintain udder health, antimicrobial therapy is not effective or not necessary for resolution of many cases of mastitis. As the use of antimicrobials has declined, many alternative treatments have been explored, but few non-antimicrobial treatments have documented efficacy. The purpose of this paper is to review the concepts of antimicrobial stewardship on dairy farms from the US perspective, with an emphasis on current and future management strategies for udder health.

尽管抗菌药物在奶牛中的使用受到严格限制，但对耐药细菌的发展和传播的担忧导致了对乳腺炎治疗的重新审查。在过去，几乎所有的临床乳腺炎病例都使用乳内抗生素对症治疗，在许多地区，大多数奶牛在干燥时接受乳内抗生素治疗。在现代奶牛场，病原体分布的变化减少了对所有乳腺炎病例使用抗菌剂的需要。非严重临床乳腺炎的培养引导选择性治疗方案已在许多农场采用，并与抗菌药物管理原则保持一致。虽然需要一些抗菌治疗来维持乳房健康，但抗菌治疗对许多乳腺炎病例的解决并不有效或没有必要。随着抗菌素使用的减少，已经探索了许多替代治疗方法，但很少有非抗菌素治疗方法具有文献记载的疗效。本文的目的是从美国的角度来审查抗菌剂管理奶牛场的概念，重点是当前和未来的管理策略，为乳房健康。

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引用次数: 0

The intersection of biology and advanced technologies defines the future of dairy reproductive management 生物学和先进技术的交叉定义了奶牛繁殖管理的未来

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0840

M.C. Lucy

Advances in reproductive management in dairy cattle have typically been made through the application of new technology. The past 25 yr have been a period of rapid improvement in dairy reproduction through the implementation of new technology that was unknown a short time ago. The next 25 yr will likely be similar with the refinement of existing technology and development of new technology to address the current challenges to dairy reproduction. Many of these new developments will address the need for greater on-farm automation necessitated by the consolidation of farms (more cows per farm) in the face of shortages in large animal veterinary and agricultural labor. Genomics will continue to play an important role in improving fertility on farm. There is the possibility that postpartum uterine health could benefit from advanced technologies that are emerging as effective treatments for tissue damage caused by disease. The reprogramming of somatic cells into gametes (in vitro gametogenesis) or embryos (blastoids) may entirely change the methods used to propagate elite genetics from female animals. Despite important advances in new technology, there are also important questions and researchable topics that need to be addressed so that the field of dairy reproduction can advance. These include automating or simplifying the current method of artificial insemination, addressing the short lifespan of sperm in the reproductive tract, and solving fertilization failure and embryonic loss following insemination. Embryo technologies await new discoveries to improve embryo yield from donor animals, increase the development of embryos in culture, reduce the damage caused by freezing embryos, and effectively evaluate embryo quality before transfer. The collective result of new knowledge and new technology will drive further improvements in genetics, fertility, and the efficiency of reproduction in high-producing dairy cattle.

奶牛繁殖管理的进展通常是通过新技术的应用取得的。在过去的25年里，由于实施了不久前还不为人知的新技术，奶牛的繁殖得到了迅速改善。未来25年很可能与现有技术的改进和新技术的开发相似，以应对当前奶牛繁殖面临的挑战。在面临大型动物兽医和农业劳动力短缺的情况下，由于农场合并（每个农场更多的奶牛），许多新的发展将解决对农场更大自动化的需求。基因组学将继续在提高农业肥力方面发挥重要作用。产后子宫健康有可能受益于先进技术，这些技术正在成为疾病引起的组织损伤的有效治疗方法。体细胞重编程为配子（体外配子发生）或胚胎（囊胚）可能完全改变用于从雌性动物繁殖精英遗传的方法。尽管新技术取得了重大进展，但仍有重要的问题和可研究的主题需要解决，以便奶牛繁殖领域能够向前发展。这些包括自动化或简化目前的人工授精方法，解决精子在生殖道中寿命短的问题，以及解决授精后受精失败和胚胎丢失的问题。胚胎技术正在等待新的发现，以提高供体动物的胚胎产量，增加胚胎在培养中的发育，减少胚胎冷冻造成的损害，并在移植前有效地评估胚胎质量。新知识和新技术的共同成果将推动高产奶牛的遗传、生育力和繁殖效率的进一步提高。

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引用次数: 0

The future of milk in 2050: Dairy in the age of personalization 2050年牛奶的未来：个性化时代的乳制品

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0859

Eve Pollet

Cow milk is often considered one of the most versatile foods on the planet, with an ability to transform into multiple formats, containing thousands of bioactive compounds that serve a plethora of different purposes in the body, some of which are known, and many of which are still to be discovered. In the past 25 years, dairy has continued to be recognized as a highly nutrient-dense commodity. Advancements in the next 25 years will push culture and consumers toward enhanced demands for precision, personalization, and transparency from the products they purchase to the services they use, especially regarding food, health, and wellness. This will begin the shift for dairy and milk from a nutrient-dense commodity to an even higher value food. Dairy foods will need to align with new concepts in the future of retail and commerce that allow consumers to gain tailored solutions based on a set of criteria and personal preferences they set, with and through their personal technology. Dairy science will play a critical role in enabling this shift—encompassing fields from nutrition science and product development to genetics, marketing, and commercialization—by leveraging the versatility of cow milk and demonstrating dairy food's health and wellness benefits from the molecular level to the whole dairy matrix.

牛奶通常被认为是地球上最通用的食物之一，它能够转化成多种形式，含有数千种生物活性化合物，对人体有多种不同的用途，其中一些是已知的，还有许多有待发现。在过去的25年里，乳制品一直被认为是一种营养丰富的商品。未来25年的进步将推动文化和消费者对从他们购买的产品到他们使用的服务的精确度、个性化和透明度的更高要求，特别是在食品、健康和保健方面。这将开始使乳制品和牛奶从一种营养丰富的商品转变为一种价值更高的食品。乳制品需要与未来零售和商业的新概念保持一致，使消费者能够根据他们设定的一套标准和个人偏好，通过他们的个人技术获得量身定制的解决方案。通过利用牛奶的多功能性，从分子水平到整个乳制品基质，展示乳制品对健康和保健的益处，乳制品科学将在实现这一转变（从营养科学和产品开发到遗传学、营销和商业化）的过程中发挥关键作用。

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引用次数: 0

Genomics and phenomics: Who will be the dairy cows of the future? 基因组学和表型学：谁将是未来的奶牛？

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0872

Luiz F. Brito, Allan P. Schinckel, Hinayah Rojas de Oliveira

The dairy industry has experienced unprecedented genetic progress, more than doubling milk yield over recent decades, but this has often resulted in reduced fertility, longevity, and robustness. This review addresses the question “Who will be the dairy cows of the future?” by highlighting the integration of genomics, phenomics, and advanced breeding strategies. From our perspective, future cows are expected to be healthier, more resilient, and longer-lived, with improved fertility, feed efficiency, and reduced methane emissions. Precision technologies, wearable sensors, and automated systems are providing novel phenotypes and driving selection for adaptability, welfare, and efficiency. Genomic selection, reproductive and other biological technologies, and beef-on-dairy crossbreeding are reshaping dairy breeding programs, while collaborations are critical for advancing multiple-trait evaluations and safeguarding genetic diversity. Despite Holstein breed dominance, maintaining across- and within-breed variation is essential for long-term sustainability. Ultimately, as a consequence of the wide adoption of precision technologies, more complex breeding goals, and effective breeding strategies, the dairy cow of the future will balance productive efficiency with resilience, welfare, and environmental efficiency, ensuring global sustainability of dairy production.

乳制品行业经历了前所未有的遗传进步，近几十年来牛奶产量增加了一倍多，但这往往导致生育力、寿命和健壮性下降。这篇综述通过强调基因组学、表型组学和先进育种策略的整合，解决了“谁将是未来的奶牛”这个问题。从我们的角度来看，未来的奶牛将更健康，更有弹性，更长寿，生育能力提高，饲料效率提高，甲烷排放量减少。精密技术、可穿戴传感器和自动化系统为适应性、福利和效率提供了新的表型和驱动选择。基因组选择、生殖和其他生物技术以及牛奶杂交正在重塑奶牛育种计划，而合作对于推进多性状评估和保护遗传多样性至关重要。尽管荷斯坦犬的品种优势，保持品种间和品种内的变异对长期的可持续性至关重要。最终，由于精密技术的广泛采用、更复杂的育种目标和有效的育种策略，未来的奶牛将在生产效率与适应力、福利和环境效率之间取得平衡，确保全球乳制品生产的可持续性。

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引用次数: 0

Making future udders: Mammary development and perinatal programming of dairy cattle 制造未来的乳房：奶牛的乳房发育和围产期规划

IF 2.2

JDS communications

Pub Date : 2025-12-01 DOI: 10.3168/jdsc.2025-0828

Jimena Laporta, Maverick C. Guenther

The perinatal period, described herein as the time spanning the final 2 mo of gestation through 2 mo postnatal, is a critical window of developmental plasticity for many organs in placental mammals, including the mammary gland (MG). In dairy cattle, early-life MG development involves foundational morphogenic events that are highly sensitive to environmental and nutritional factors. Emerging evidence challenges the long-standing belief that substantial MG development begins after weaning and lasts until puberty, showing instead that preweaning mammary parenchymal (mPAR) growth is allometric and its degree of development can influence future lactational capacity. Overall BW typically doubles from birth to 60 d, whereas both whole udder weight and the mammary fat pad increase by ∼2.2 to 3 times over the same period. In contrast, the mPAR exhibits pronounced allometric growth, expanding 15 to 35 times during this time. Early-life management strategies, such as heat abatement to maintain thermal homeostasis and enhanced nutrition through higher milk intake supporting greater average daily gain, further promote mPAR development and can positively influence future lactation performance of dairy cows. These findings underscore the importance of integrating developmental biology into heifer-rearing strategies and emphasize the need for precise environmental and nutritional management during this critical window to support lifelong mammary function and optimize herd performance.

围产期是指从妊娠最后2个月到产后2个月的时间，是胎盘哺乳动物许多器官发育可塑性的关键时期，包括乳腺（MG）。在奶牛中，生命早期MG的发育涉及对环境和营养因素高度敏感的基础形态发生事件。新出现的证据挑战了长期以来的观点，即大量MG的发育始于断奶后并持续到青春期，相反，断奶前乳腺实质（mPAR）的生长是异速生长的，其发育程度会影响未来的泌乳能力。从出生到60天，总体体重通常增加一倍，而同期全乳重和乳腺脂肪垫均增加约2.2至3倍。相比之下，mPAR表现出明显的异速生长，在此期间扩张15至35倍。早期生命管理策略，如通过减热维持热稳态和通过增加牛奶摄入量支持更高的平均日增重来增强营养，可以进一步促进mPAR的发育，并对奶牛未来的泌乳性能产生积极影响。这些发现强调了将发育生物学纳入小母牛饲养策略的重要性，并强调了在这一关键窗口期进行精确的环境和营养管理的必要性，以支持终身乳腺功能和优化群体表现。

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引用次数: 0

Common misinterpretations of statistical significance and P-values in dairy research 乳制品研究中对统计显著性和p值的常见误解

IF 2.2

JDS communications

Pub Date : 2025-09-25 DOI: 10.3168/jdsc.2025-0835

R. Laven , D.A. Yang

Careful communication of results is integral to dairy research. However, many published studies contain misinterpretation of the results of statistical analysis, which can lead to conclusions being drawn which are not consistent with the data. Many of these interpretations have arisen because of a focus on P-values rather than on the potential range of effects that are compatible with the study data. This review focuses on 3 misinterpretations: the use of levels of statistical significance to compare results between or within studies, overinterpretation of nonsignificant results, and the use of “trend” to describe results that are “close” to a significance threshold. All of these misinterpretations can be avoided by paying more attention to the range of effects that are compatible with the data. Such a focus will have many benefits—not least, making it clearer when studies have insufficient power to accurately characterize their outcomes. Focusing on compatible effects is not a panacea but will improve statistical inference and provide more thoughtful descriptions of study outcomes.

仔细沟通结果是乳品研究不可或缺的一部分。然而，许多已发表的研究包含对统计分析结果的误解，这可能导致得出与数据不一致的结论。这些解释中的许多都是由于关注p值，而不是关注与研究数据相容的潜在影响范围。这篇综述着重于三种误解：使用统计显著性水平来比较研究之间或研究内部的结果，对不显著结果的过度解释，以及使用“趋势”来描述“接近”显著性阈值的结果。所有这些误解都可以通过更多地关注与数据兼容的影响范围来避免。这样的关注有很多好处——尤其是，当研究没有足够的力量来准确地描述其结果时，它会更清晰。关注相容效应不是万灵药，但会改善统计推断，并提供更周到的研究结果描述。

引用次数: 0